{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "matchzoo version 1.0\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matchzoo as mz\n",
    "print('matchzoo version', mz.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "`classification_task` initialized with metrics [accuracy]\n"
     ]
    }
   ],
   "source": [
    "classification_task = mz.tasks.Classification(num_classes=2)\n",
    "classification_task.metrics = ['acc']\n",
    "print(\"`classification_task` initialized with metrics\", classification_task.metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "data loading ...\n",
      "data loaded as `train_pack_raw` `dev_pack_raw` `test_pack_raw`\n"
     ]
    }
   ],
   "source": [
    "print('data loading ...')\n",
    "train_pack_raw = mz.datasets.wiki_qa.load_data('train', task=classification_task)\n",
    "dev_pack_raw = mz.datasets.wiki_qa.load_data('dev', task=classification_task)\n",
    "test_pack_raw = mz.datasets.wiki_qa.load_data('test', task=classification_task)\n",
    "print('data loaded as `train_pack_raw` `dev_pack_raw` `test_pack_raw`')"
   ]
  }
 ],
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